System and method for heterogenous spectrum sharing between commercial cellular operators and legacy incumbent users in wireless networks

ABSTRACT

Described herein are systems and methods for telecommunications spectrum sharing between multiple heterogeneous users, which leverage a hybrid approach that includes both distributed spectrum sharing, spectrum-sensing, and use of geo-reference databases.

FIELD

This disclosure relates to a system and method for wirelesscommunication spectrum sharing.

BACKGROUND

The proliferation of smartphones and other mobile devices has placedheavy data traffic demands on cellular networks, with cellular networkoperators facing difficult challenges in meeting this demand given theirexisting spectrum allocations. Recent policy shifts at the federallevels and Department of Defense indicate that sharing existing federalspectrum with commercial users may be a viable option for meaningfulincrease of spectrum for Long Term Evolution (LTE) fourth generation(4G) cellular technologies. Making more spectrum available willcertainly provide opportunities for mobile broadband capacity gains, butonly if those resources can be efficiently accessed such that secondaryusers can proactively share the same bands as the primary users (e.g.,federal incumbent users). Effectively grafting pre-emptible spectruminto a cellular network is challenging. Past approaches to coexistencewith primary users centered on spectrum sensing-based dynamic spectrumaccess (DSA) techniques and database driven DSA techniques.

Spectrum sensing DSA approaches entail the use of sensing devices toscan a frequency band of interest to identify unused spectrum wheresecondary access is possible without impacting primary user operations.The main approaches can be categorized as internal (co-located) sensing,external sensing, use of beacons, and database driven techniques, andhave included algorithms for matched filtering, energy detection,cyclostationarity, radio identification based sensing, waveform basedsensing, etc. So-called cooperative spectrum sensing increases sensingaccuracy by fusing data from multiple nodes and thus takes advantage ofspatial diversity. General types of cooperative spectrum sensing includecentralized, distributed, external, or device centric (local) sensing.

Database driven DSA is a sub-class of the sensing based DSA approach.The database driven approach is classified into two general categories:geo-location based and interference based. Both are similar in principlethat they provide a database to the secondary users (cellular networkoperators) which helps them transmit in licensed bands while ensuringthey do not interfere with primary users in the given band. Thesedatabases can be stored at eNodeBs or at the network level and havedifferent levels of granularity. In the past, these databases onlyprovided coarse resolution of historical spectrum use by primary users.A type of database called a radio environment map (REM), which cancontain interference information, have been utilized to help indeploying secondary networks. However, each of these approaches hasshortcomings, especially when mobile users, hidden nodes, andinteraction with the incumbent or primary users are considered.

Therefore a need exists for an improved system and method for temporaland geographical spectrum sharing between a commercial cellular operatorand a government incumbent operator.

SUMMARY OF THE INVENTION

Described herein are systems and methods for spectrum sharing betweenmultiple heterogeneous users, which leverage a hybrid approach thatincludes both distributed spectrum sensing and use of geo-referencedatabases. A hybrid approach can be thought of as a combination ofdynamic spectrum sensing with use of a radio environment map (REM) withlocal sensing information. This approach allows opportunistic access togovernment spectrum bands in a controlled manner, utilizing both DSAsensing and database interaction, to maximize fallow spectrum whilesimultaneously minimizing the potential for interference to incumbentusers.

As a general overview, commercial cellular operators seeking additionaltemporary frequency allocations perform an analysis incorporatingspectrum sensing to identify potential primary users. This sensing canoccur at the base station, at the end user, or at a new networkcomponent in communication with at least one base station. Cellularoperators send a request query to a federal database server connected todatabases having information on temporal and geographical spectrumassignments and any potential interference. Incumbent federal spectrumusers typically include government entities. After an interferenceanalysis, the federal database server assigns temporary spectrumallocations that are unique in time and geographic location. Allocationof the assigned spectrum bands is performed using a two-tier approach toallocate resources to users. A first tier allocation process allocatesresources to cell zones, and a second tier process allocates resourcesto users in their respective cell zones.

Efficient space-time spectrum utilization can thus be achieved between aprimary user (denoted by PU, i.e., the government incumbent operator)and a secondary user (denoted by SU, i.e., the cellular operator) whilemaintaining the interference experienced by the primary user below aparticular threshold. Further, a low-latency protocol for interactionbetween a spectrum server and a federal database server ensures that thespectrum server is notified in almost real time, if required to preempta prior spectrum allocation. Parameters for a spectrum lease request aredetermined with an objective of maximizing the network utility derivedfrom the requested spectrum. The spectrum server honors a set oftransmission restrictions associated with the allocated primary spectrumby incorporating the restrictions into the spectrum allocationalgorithms at the spectrum server and at an eNodeB level. The two-tierapproach for resource allocation among users is utilized which resultsin a slightly suboptimal but more tractable solution compared to a jointresource allocation scheme. A first tier allocation process allocatesresources to cell zones, and a second tier process allocates resourcesto users in their respective cell zones.

The resource allocation process at the spectrum server attempts tomaintain an acceptable QoS (quality of service) for users while stillsatisfying the capacity demand of the users within the cells of thecellular network. To this end, a fractional frequency reuse (FFR) schemeis proposed in which each cell is divided into zones: a center cell zoneand three cell-edge sector zones. This process takes as feedback a novelmetric called the average demand factor from each eNodeB under thespectrum server's control. This metric models the rate requirement ofcapacity deficient users at cell-edge zones and thus ensures fairness inallocation of resources to each of the four zones. The calculation ofthe fractional utility metric is unique in a way that makes it easy toincorporate federal restrictions and local sensing decision variables.

The eNodeB level resource allocation method allocates resources toindividual users within each zone. The eNodeB calculates instantaneousdemand factors of each user within the cell and stores these values. Thedemand factors are averaged over time and users and fed back to thespectrum server whenever needed for operation of the resource allocationprocess. This leads to appreciable reduction in communication overhead.The fairness among the users is introduced using a weighted linearutility function. User allocation is achieved by solving a linearinteger programming problem instead of a typical non-linear integerprogramming problem, thereby significantly reducing complexity whilesettling for a slightly suboptimal (in terms of fairness) solution. Thetime-interval between two executions of the eNodeB level allocationprocess is flexible and thus allows the process to run at different timescales, as desired.

BRIEF DESCRIPTION OF FIGURES

FIG. 1 is a block diagram of an exemplary system for spectrum sharingand illustrates the infrastructure of a commercial cellular operatorusing LTE technology, and includes a spectrum server in communicationwith a federal database server;

FIG. 2 is a flow diagram of interaction between the LTE wireless system,the spectrum server, and the federal database server of FIG. 1 as partof a process for spectrum sharing;

FIG. 3 is an illustration of an exemplary signaling exchange implementedfor initialization, registration, allocation request, and validationbetween the spectrum server and the federal database server;

FIG. 4 is a flow diagram of an exemplary process for estimating thebandwidth demand of an LTE network and determining the available primaryspectrum to prepare a spectrum lease request to obtain a spectrum leasefrom the federal database server;

FIG. 5 is a flow diagram of an exemplary level one process forallocation of leased frequency bands to cell zones of the LTE wirelesssystem by a radio network controller;

FIG. 6 is a flow diagram of an exemplary level two process forallocation of frequency bands to users within single cell zones of theLTE wireless system;

FIG. 7 is a flow diagram providing more detail about the exemplaryallocation request process illustrated in FIG. 4 between the spectrumserver and the federal database server;

FIG. 8 is a flow diagram providing more detail for steps 501, 502, 503of the exemplary allocation request process illustrated in FIG. 5, andwhich includes calculating the utility function, determining fractionalutility, and quantifying capacity requirements; and

FIG. 9 is a flow diagram of an exemplary process for calculating variousitems of block 802 of FIG. 8, which occurs as periodic interactionbetween the spectrum server and multiple eNodeBs.

DETAILED DESCRIPTION

As an overview, the systems and methods described herein present anapproach for enabling spectrum sharing between a government user and acommercial cellular operator. The main components of the system includethe commercial radio access network, the commercial packet core, aspectrum server having interaction with a federal database servercontrolled by a government entity, and sensors that provide real-timespectrum sensing and interference monitoring. In general, a commercialnetwork is able to make requests for additional spectrum resources tosupport the demands of end users. A spectrum server will make requeststo a federal database server that has knowledge of the incumbent usersprovided from a master government file and knowledge of interferencewith respect to the incumbent users. In conjunction with the databaseknowledge, information regarding real-time spectrum sensing performedlocally at commercial base stations is used to award spectrum resourceallocation to the commercial base stations. This system and methodassume that the commercial end users, such as handsets, and basestations are capable of operating on the available government spectrum.The awarded government spectrum resource is provided to the commercialcellular operator for use by the base stations to supplement theirexisting spectrum. These awards may include temporal, geographical, andoperational constraints such as maximum power transmission. It isenvisioned that this additional spectrum can provide additionalresources for low priority data. In the event that the incumbentgovernment user requires the awarded spectrum, the commercial cellularoperator will be required to vacate the awarded allocation. The novelcontributions of this system include the method for requestingresources, determining how much and which band to request, and theprocess for allocating awarded resources to base stations and end users.

Referring to FIG. 1, an exemplary system 100 for spectrum allocation isshown in which a commercial cellular operator has deployed an LTEarchitecture. System 100 includes a radio access network (RAN) 102,represented here by LTE E-UTRAN, which is comprised of individualenodeB's 104 a-c, interconnected through the X2 interface 106. The RAN102 connects to an evolved packet core represented by a mobilemanagement entity (MME) 110. The connection is enabled through the S1interface 108. In this exemplary system, end user elements, such ashandsets, which are either mobile or static, interact with the RAN 102.Data schedulers, residing in the enodeB's, are used to coordinatetransmissions of voice or packet data to the end user elements, denotedas secondary users. Sensors 122 perform spectrum sensing at the basestations to determine the possible presence of federal incumbent users,whose presence may not be known with certainty in advance due to theirmobility, and/or failure to update a federal database.

A proposed spectrum server 114 interfaces with the RAN through theOperations and Maintenance (OAM) interface 109. The spectrum server 114connects via secure connection 116 with a federal portion of the system100, which includes a federal database server 118, database 112, anddatabase 120. From a functional perspective, the spectrum server 114aggregates the needs of the base stations, makes requests to the federaldatabase server 118, and manages any awarded spectrum back to theindividual base station. Federal interference sensors 123 provideinterference sensing on the federal side, such as to detect anyinterference with federal systems.

More specifically, federal database server 118 interacts with databases112 and 120. Database 120 is a real-time interference reportingdatabase. The federal database server 118 performs an interferenceanalysis prior to a spectrum allocation, using information from thisdatabase. This database also provides information important forrevocation of spectrum. For example, if a government radar system startsto sense that it is being interfered with, and it is due to a previousspectrum allocation to a commercial operator, an interference analysiswill drive the federal database server to revoke or constrain thatprevious allocation. The federal database server does not provideinformation about its operations, rather it will only approve, ordisapprove requests and may add constraints to any approved allocation.

Database 112 includes one or more enhanced Government Master Files,which includes information on temporal and geographical spectrumdynamics. Currently, a primitive Government Master File (GMF) existswhich is basically a list of spectrum allocations and their locations.An enhanced version of such a file can also include information of whenvarious users are operating, including such factors as duty cycle, powerof the system, antenna beam pattern, and so on. The federal databaseserver can also incorporate this information into allocation decisions.For example, if a spectrum band is typically devoted to the Army but theArmy only uses it for special training exercises at certain times, thefederal database server can allocate the band for specific other times.Similarly, if a satellite system only transmitted data once every hourfor two minutes, then there is a significant period of idle time forthat band that could be allocated to a commercial operator.

Regarding operation of this system, novel contributions include thehybrid interaction between spectrum sensing and database driven DSAapproaches. Leveraging both techniques yields the ability tocharacterize the position, directionality, power, and modulation ofrelevant emitters in a localized region. An additional novelcontribution includes the use of radio environment mapping by thespectrum server that integrates current sensing data from base stationsensors 122 and historical spectrum sensing data from eGMF 112. Further,incorporating real-time interference knowledge enables the use ofinitial conservative interference assumptions when allocating governmentspectrum. These interference assumptions can gradually grow less strictuntil the spectrum sensing identifies interference. This approachenables online tenability of propagation models and truer interferencethresholds, which are difficult to capture in analytical models. Thisapproach is a novel contribution over existing state-of-the-art designsimplementing static approaches. The implications include enabling accessto significant amount of additional spectrum for commercial use.

Referring to the system in FIG. 2, a spectrum sharing process of system100 starts with the network, represented here by the spectrum server114, which can be located in the enhanced packet core (EPC), issuing alease request 204 for spectrum allocation to the federal database server118 (an exemplary request process is further explained with respect toFIG. 4). The federal database server 118 makes a decision regardingwhat, if any, spectrum resources are available by performing an analysis206, including an interference analysis. Any spectrum availability willbe further specified with restrictions on time length, location, power,and most importantly, whether or not the commercial user will haveunrestricted access or if the commercial user must also perform spectrumsensing and leave the band if it detects a primary user. The federaldatabase server takes into account several different types ofinformation in order to make any awards to the spectrum server 114. Asmentioned, assessment of any interference to federal incumbent users isone element that affects the decision process for awarding resources tothe spectrum server or for changing existing allocation. For example, ifa previous request for spectrum was approved by the federal databaseserver, and an updated interference analysis shows that a federal useris being impinged upon, the federal database server may revoke orfurther restrict an allocation. The overall decision process by thefederal database server incorporates broad parameters in the decisionsuch as the need for operational security, fairness in allocatingresources to secondary users, and determining dynamic interferencemitigation procedures. Upon completion of the analysis, the federaldatabase server returns initial allocations 208 back to the spectrumserver. This allocation may incorporate several constraints, includingdetection thresholds that define criteria for vacating a band in aspecific sub-region.

The spectrum server 114 can incorporate spectrum-sensing input 210 fromsensors 122 at the base stations in the RAN 102, both in the leaserequest and as part of a resource optimization process 202. The sensingfrom the RAN is conveyed at 212 to the spectrum server 114 forassimilation into a radio environment map (REM). A REM can be as simpleas a table of location, time, and energy detected. It can be used totrack historical and geo-located spectrum data. For example, every dayat 5 PM at a major office park, cell phone usage peaks as people leavefrom work to head home. However, at 6 PM, there may be little cell phoneusage. As another example, near a construction site there may beinterference from high-powered welding during work hours, but littleinterference during non-work hours. This REM can provide more data foran artificial intelligence decision making algorithm to make moreinformed decisions. The REM can include items such as location, time,day, strength of signal, whether users are mobile and when, traveldirections, and so on. This information can be combined with geographicdata such as terrain, tree cover, season of the year (summer=highfoliage, autumn/winter=no leaves), elevation, potential tall buildings,and many other possible relevant items that can affect radio signals.

In some embodiments, spectrum sensing is performed using a separateenergy detector located at each base station. In other embodiments,spectrum-sensing data is obtained from individual handsets using theMinimize Drive Test (MDT) capability in release 10 of the LTE standards.The MDT capability enables functionality for enodeB's to poll end userdevices for received signal strength data. The returned signal strengthcan be used by the spectrum server to populate REM profiles.

The REM and the spectrum allocation information 208 are used in aresource optimization process 202. The results of the optimization takethe form of resource allocation 216 that is sent back to individual basestations in the RAN 102. The network continually performs thesensing/resource allocation process, which refines the distributionwithin the network. The federal database server 118 can provideallocation updates at block 222, including revoking the originalspectrum allocation under a variety of circumstances. These can includeexpiration of the original allocation, reports of harmful interferenceor a priority request from other federal users that have pressing needs,analyzed at block 220. In all cases, the spectrum server 114 can make anew allocation request.

In more detail, still referring to FIG. 2, this process flowincorporates the spectrum server 114 as an intermediate interfacebetween commercial users and disparate government incumbent users. Thepresent method and system enables the interaction between heterogeneousnetworks encompassed by systems that do not share common packet coresand only use similar spectrum allocations in geographic proximity. Pastapproaches relied on geographic exclusion zones, limited operationalcycles, or highly restrictive frequency allocations. In particular, theinteraction between the PU (controlled by the federal database server)and the SU (eNodeB controlled by the spectrum server) to achieveefficient space-time spectrum utilization maintaining the interferenceexperienced by the primary user below a particular threshold is uniqueto this area. Further novelty involves the use of a unique combinationof several network parameters to prepare the spectrum lease. Theseparameters include available PU bands, average traffic volume, andquality of service (QoS) requirements of active users. These parametersare factored in while preparing the spectrum lease request. This schemeis quite flexible in the sense that it takes into account differentpossible spectrum lease formats (specified by the federal databasesever) while preparing the spectrum lease request. The parameters forthe spectrum lease request are determined with an objective ofmaximizing the network utility derived from the requested spectrum. Thespectrum server honors the transmission restrictions associated with theallocated primary spectrum by incorporating this information into thespectrum allocation algorithms at the spectrum server and eNodeB level.

The present method and system provided herein provides a coordinationmechanism between heterogeneous systems, which permits spectrumcoexistence in real-time without highly restrictive frequencyallocations. In particular, the interaction between a PU (PrimaryUser—controlled by federal database server) and the SU (SecondaryUser—via eNodeB's controlled by spectrum server) to achieve efficientspace-time spectrum utilization while maintaining the interferenceexperienced by the primary user below a particular threshold is a newfeature. Further novelty involves the use of a unique combination ofseveral network parameters to prepare the spectrum lease. Theseparameters include available PU bands, average traffic volume, andquality of service (QoS) requirements of active users. These parametersare factored in while preparing the spectrum lease request. This schemeis quite flexible in the sense that it takes into account differentpossible spectrum lease formats (specified by the federal databaseserver) while preparing the spectrum lease request. The parameters forthe spectrum lease request are determined with an objective ofmaximizing the network utility derived from the requested spectrum. Thespectrum server honors the transmission restrictions associated with theallocated primary spectrum by incorporating this information into thespectrum allocation algorithms at the spectrum server and eNodeB level.

Referring to FIG. 3, an exemplary signaling exchange implemented forinitialization, registration, allocation request, and validation betweenthe spectrum server 114 and federal database server 118 is shown.Database discovery starts with location of a uniform resource identifierthat uniquely identifies a specific database server. The initializationprocess 300 consists of a pair of messages including an initial servicerequest 302 and initial response 304. This exchange enables the spectrumserver to information such as capabilities, regulatory domain, and thedesired sequence of protocol operations. The spectrum server 114 willalso obtain authentication parameters from the federal database server118 that will enable the spectrum server to prove its authenticity andprovide message integrity during the entire protocol operation. Afterthe initialization process, the spectrum server and federal databaseserver exchange another pair of messages as part of the registrationprocess 310. The registration exchange establishes operationalparameters as required by the spectrum management authority, such as theFederal Communications Commission. Parameters can include owner and/oroperator contact information, location and antenna height parameters.This registration process is required upon initial contact or whenoperational parameters change. The registration message pair consist ofa registration request 312 and a registration response 314. The nextstep after the registration and mutual authentication is a query messageprocess 320. The spectrum server sends an available channel query 322that includes required parameters, such as geo-location. The federaldatabase server returns an available channel response 324 that includesan array of available channels (spectrum bands) within the scope of therequest and regulatory authority. Information in the array includes thefrequency range, availability rating, operating power, and eventmanagement. The spectrum server 114 must then inform the federaldatabase server 118 via a use channel notify communication 326 toindicate channels it intends on using at specific enodeB's in thenetwork. The federal database server acknowledges with a use channelresponse 328. Finally, the enodeB's under control of the spectrum serverrequire validation 332 by the federal database server. By FCC rules, aspectrum server can allocate secondary spectrum after enodeB's areregistered in the database. Therefore the federal database serversupports the validation by responding with an acknowledgement 334.

Referring to FIG. 4, an exemplary process is illustrated for estimatingthe bandwidth demand of an LTE network and determining the availableprimary spectrum to obtain with a spectrum lease from the federaldatabase server. This process occurs in the LTE network after thespectrum server 114 gets the registration response 314 from the federaldatabase server. and before it sends the channel query 322. In general,this requires a determination of the activity of both primary users andsecondary users.

At a step 401, each eNodeB, during a sensing interval, independentlysenses the activity of primary users (PU) in all known PU bands. Then atstep 402, each eNodeB sends soft or hard decisions (as required)regarding the activity to the spectrum server 114. Then at step 403, foreach PU band, the spectrum server optimally combines the sensingdecisions from all the eNodeBs and prepares a set of available bands,denoted by A.

At a step 404, each secondary user reports its uplink capacityrequirements and channel-quality-indicator (CQI) metric to its servingeNodeB which then maps it to the user's bandwidth demand. At a step 405,each eNodeB computes the bandwidth required to serve all active users inaddition to the currently available spectrum. At step 406, each eNodeBreports its bandwidth requirement to the spectrum server, which thencomputes the additional spectrum to be requested (Wlease) from thefederal database 406. The spectrum server also computes the timeduration (Tlease) for which this additional spectrum needs to berequested based on the requirements of eNodeBs. At a step 407, it isdetermined whether a structured or unstructured lease request isrequired by the federal database server. In the case of a structuredlease request, at a step 408, the spectrum server additionallydetermines a minimum number of available PU bands R (R⊂A) that ifgranted access to, would completely meet the overall bandwidthrequirements. It then sends the spectrum lease request (R; Wlease;Tlease) to the federal database server at a step 409. In the case ofunstructured lease request, the spectrum server sends (Wlease; Tlease)to the federal database at a step 410. In either case, the procedurethen terminates at 412. FIG. 4 thus illustrates an exemplary method forestimating bandwidth demand of an LTE network and identifying a neededrequest for resources.

FIG. 5 is a flow diagram of an exemplary process for resource allocationof frequency bands provided by the federal database server, to the cellcenter zone or cell-edge zones (sectors) of the eNodeBs. The spectrumserver performs this allocation, which is termed a Level 1 algorithm.This process repeats every T_(eNB) transmission time interval (TTI). Astep 501 is an initialization step, which requires input from the eNodeBat step 502, namely, the average achievable rates for each end user (UE)UE-base station pair, the minimum per-UE capacity requirements, thedemand factors of the UEs, and the local sensing decisions for eachcell-center zone and cell-edge sector zone. Initialization also requiresinput from the federal database server at step 503, namely, the spectrumbands to be used for allocation and the restrictions on thetransmissions within each cell center zone or sector, which are modeledas binary federal decision variables. Further details regarding steps501, 502 and 503 are provided with respect to FIG. 8, described below.

In general, during initialization step 501, all the sub-bands areallocated to a set C_(init). For each sub-band UE pair, a utilityfunction for assigning band n to a UE within the cell center zone or toa cell-edge zone (sector) is calculated. The fractional utility gaingives the utility of assigning the n-th band to the cell-edge zonesrather than the center. The capacity requirement for each of thecell-edge zones and the cell-center zone are calculated. The sub-bandsavailable for allocation are initialized to a set Z. Two variablesmodeling increase in allocated capacity of cell-center and cell-edgezones are declared and initialized to zero. The algorithm iterates overeach sub-band. At each iteration, a sub-band is allocated to thecell-center zone or a cell-edge zone.

Still referring to FIG. 5, at step 504, the algorithm begins for then=1-st band. At step 504, the sectors 1 with capacity deficiency, (i.e.,when the difference between required capacity and the capacity incrementvariable is greater than zero) are identified for the n-th sub-band, andprocessing proceeds to a step 505. At step 505, a determination is madewhether there are any sectors with capacity. If so, processing proceedsto step 506. If not, processing proceeds to step 508. At step 506 thesector-band pair (1_, n) that gives the maximum fractional utility forassignment of the sub-band is identified and processing proceeds to step507. At step 507, it is checked whether maximum fractional utility isnegative and the center zone is capacity deficient. If yes, theprocessing proceeds to step 508. If no, processing proceeds to step 509.At step 508, the sub-band n is assigned to the cell-center zone, thevariable modeling capacity increment of the cell-center zone is updatedto reflect the assigned capacity of the n-th sub-band and the processingproceeds to step 510. At step 509, the sub-band n is assigned to sector1*, the capacity increment variable for sector 1* is updated to reflectthe assigned capacity of the n-th sub-band and the processing proceedsto step 510. At step 510, the assigned sub-band is removed from the setZ of sub-bands available for allocation and processing proceeds to step511. At step 511, a determination is made whether the set Z is empty orif the capacity requirement of center and sector zones is satisfied. Ifyes, then the process ends at 512. If not, then the process loops backto step 504 and reiterates for n=n+1. The output of the algorithm is theallocation of sub-bands in a cell-center zone or one of each of thethree cell-edge zones. This information is then input to the Level 2algorithm as described with respect to FIG. 6.

FIG. 5 thus describes an exemplary process for allocating resourcesbetween the cell center and cell edge users. The spectrum server managesfunctions that include: determining resource needs of multiple users,making requests to a federal database server, and allocating awardedresources back to users. The resource allocation algorithm at thespectrum server tries to maintain an acceptable QoS for users whilestill satisfying the capacity demand of the users within the cells. Thealgorithm divides each cell into a center zone and three sector zones.The algorithm takes as feedback a novel metric called the average demandfactor from each eNodeB under the spectrum server's control. The eNodeBscompute this metric for each center and sector zone over multiple users(averaged over multiple transmission time intervals (TTIs)). This metricmodels the rate requirement of capacity deficient users at cell-edgezones and thus ensures fairness in allocation of resources to each ofthe four zones. The calculation of the fractional utility metric is alsounique in a way that it makes it easy to incorporate the federal andlocal sensing decision variables.

FIG. 6 illustrates an exemplary process for allocation of frequencybands to users within a single cell zone, which runs at each eNodeB, andincorporates a so-called level 2 algorithm. This process is initializedat a step 601, includes as input from block 602 the allocations of bandsto cell center zones and sectors (which are determined from the level 1algorithm), and also includes as input the federal resource allocationdecision variables from block 603 (illustrated in block 802 of FIG. 8).

The initialization stage fuses the local sensing decisions and federaldecision variables to allocate resources to select users withinpermitted transmission zones. The algorithm begins at block 604. Thealgorithm has two modes—a proportional fairness mode and a linearutility maximization mode. At a step 605, a decision is made whether theproportional fairness model is to be used. If proportional fairness isused, processing proceeds to a step 606, if not, processing proceeds toa step 607. At step 606, a linear utility function, utilizing demandfactors to enforce fairness, is calculated for each user within thepermitted transmission zones of the cell, and processing then proceedsto a step 608. At step 607, a linear utility function, similar to block606 but without the demand factor, is calculated for each user withinthe permitted transmission zones of the cell, and processing proceeds tostep 608. At step 608, an integer program is solved for linear utilitymaximization to find the optimal resource allocation in terms of theBoolean variable. From step 608, processing proceeds to step 609. Atstep 609, the algorithm checks if the allocation of bands from thespectrum server is unchanged. If yes, then processing ends in block 610.If no, processing proceeds to step 604 and repeats with the newallocation. The Level 2 algorithm runs at every TTI while the Level 1spectrum server algorithm runs for a time period constituting multipletransmission intervals. The spectrum server monitors the utility offrequency allocation at each eNodeB and runs the Level 1 algorithm eachtime the utility decreases, or until the federal lease expires.

Referring to the FIG. 7, more detail is provided for an exemplaryprocess for a spectrum allocation request between the spectrum server114 and the federal database server 118 such as is more generallydescribed in FIG. 4. This exemplary process is used by the spectrumserver to determine the minimal primary user (PU) bands to be requestedof the federal spectrum database server. This process starts off withinformation about available bands, A, input at step 701 and the averagebandwidth required, W_(lease), input at step 702. Then at a step 703,the set of the bands to be requested, R, is initialized as A. Utilizingthe knowledge of the duty cycle of PU, the process determines theexpected bandwidth W _(k) for each band in R at a step 704. Then at step705, W_(diff), the difference between the total expected bandwidth (if Ris requested) and the bandwidth required is calculated. Letting σ_(W)represent the standard deviation in the required bandwidth in aparticular time interval, at step 706 a check is made whetherW_(diff)>σ_(W). If no, processing proceeds to step 708, and a leaserequest (R; W_(lease); T_(lease)) is sent to the federal databaseserver, where T_(lease) is the lease duration, determined at step 709.If true, processing proceeds to step 707. At step 707, Gk=W_(diff)− W_(k) is computed for each band kin R, and processing then proceeds to astep 710. At step 710, negative values of Gk are set to −∞ (negativeinfinity). Then at step 711, a band is selected which if removedminimizes W_(diff), and processing proceeds back to step 705. In thismanner, steps are repeated to successively remove the PU bands untilW_(diff)<σ_(W) is achieved and a lease request can be sent at step 708.

FIG. 8 illustrates an exemplary process for the initialization phase, orstep 501, 502, and 503 of the Level 1 spectrum server algorithmillustrated in FIG. 5. In particular, at a step 801 (corresponding tostep 502 of FIG. 5), the spectrum server receives inputs from theeNodeBs within its network. These inputs include: average achievablerate for each physical resource block (PRB) for each cell-center orcell-edge zone over T_(eNB) TTIs; the average demand factors; theaverage capacity requirements; and the local sensing decisions (as setforth in the REM). FIG. 9 provides more detail for these calculations.

At a step 802 (corresponding to step 503 of FIG. 5), the spectrum servertakes as input the set of PRBs which can be allocated to UEs and thefederal decision variables. The initialization step 501 of FIG. 5 isdetailed in 803. All PRBs are initialized to a set C^(init). The utilityfor assigning the n^(th) PRB to the cell-center zone, W_(n) ^(c) and theutility for assigning it to the cell-sector zone 1, W_(n) ^(c(e),l) arecalculated. These utilities are average rate based utility functionsthat incorporate the average demand factor for each cell center andsector zone, the federal decision variables and the local sensingdecisions from 801. A fractional utility for assigning a PRB to a sectoras opposed to the center zone is calculated. The capacity requirementfor the cell-center and cell sector zones is calculated. The set of PRBsC^(init) is assigned to the set Z. Capacity assignment variables g^(c)and g^((e),l) are initialized to 0. These variables are used in steps508 and 509 respectively. At step 804, this process is linked to block504 of FIG. 5.

The advantages of the present method and system include, withoutlimitation, a process that incorporates hybrid interaction betweenspectrum sensing and database of incumbent users to enable spectrumsharing between heterogeneous networks. Furthermore, the present methodand system implements localized radio environment mapping as a supporttool for spectrum sharing. Specific embodiments, though not limited to,present novel approaches to identifying the need for spectrum resources,a process for interacting with a spectrum database, allocating awardedspectrum to cell centers and cell edges, and allocating these resourcesamongst users in a single cell.

In a broad embodiment, the present method and system is a method andsystem for spectrum sharing between multiple heterogeneous users. Themethod implements an interaction between a spectrum server, database ofincumbent users, and localized spectrum sensing.

While only a few embodiments of the present invention have been shownand described, it will be obvious to those skilled in the art that manychanges and modifications may be made thereunto without departing fromthe spirit and scope of the present invention as described in thefollowing claims. All patent applications and patents, both foreign anddomestic, and all other publications referenced herein are incorporatedherein in their entireties to the full extent permitted by law.

The methods and systems described herein may be deployed in part or inwhole through a machine that executes computer software, program codes,and/or instructions on a processor. The present invention may beimplemented as a method on the machine, as a system or apparatus as partof or in relation to the machine, or as a computer program productembodied in a computer readable medium executing on one or more of themachines. In embodiments, the processor may be part of a server, cloudserver, client, network infrastructure, mobile computing platform,stationary computing platform, or other computing platform. A processormay be any kind of computational or processing device capable ofexecuting program instructions, codes, binary instructions and the like.The processor may be or include a signal processor, digital processor,embedded processor, microprocessor or any variant such as a co-processor(math co-processor, graphic co-processor, communication co-processor andthe like) and the like that may directly or indirectly facilitateexecution of program code or program instructions stored thereon. Inaddition, the processor may enable execution of multiple programs,threads, and codes. The threads may be executed simultaneously toenhance the performance of the processor and to facilitate simultaneousoperations of the application. By way of implementation, methods,program codes, program instructions and the like described herein may beimplemented in one or more thread. The thread may spawn other threadsthat may have assigned priorities associated with them; the processormay execute these threads based on priority or any other order based oninstructions provided in the program code. The processor, or any machineutilizing one, may include memory that stores methods, codes,instructions and programs as described herein and elsewhere. Theprocessor may access a storage medium through an interface that maystore methods, codes, and instructions as described herein andelsewhere. The storage medium associated with the processor for storingmethods, programs, codes, program instructions or other type ofinstructions capable of being executed by the computing or processingdevice may include but may not be limited to one or more of a CD-ROM,DVD, memory, hard disk, flash drive, RAM, ROM, cache and the like.

A processor may include one or more cores that may enhance speed andperformance of a multiprocessor. In embodiments, the process may be adual core processor, quad core processors, other chip-levelmultiprocessor and the like that combine two or more independent cores(called a die).

RAM disks, Zip drives, removable mass storage, off-line, and the like;other computer memory such as dynamic memory, static memory, read/writestorage, mutable storage, read only, random access, sequential access,location addressable, file addressable, content addressable, networkattached storage, storage area network, bar codes, magnetic ink, and thelike.

The methods and systems described herein may transform physical and/oror intangible items from one state to another. The methods and systemsdescribed herein may also transform data representing physical and/orintangible items from one state to another.

The elements described and depicted herein, including in flow charts andblock diagrams throughout the figures, imply logical boundaries betweenthe elements. However, according to software or hardware engineeringpractices, the depicted elements and the functions thereof may beimplemented on machines through computer executable media having aprocessor capable of executing program instructions stored thereon as amonolithic software structure, as standalone software modules, or asmodules that employ external routines, code, services, and so forth, orany combination of these, and all such implementations may be within thescope of the present disclosure. Similarly, it will be appreciated thatthe various steps identified and described above may be varied, and thatthe order of steps may be adapted to particular applications of thetechniques disclosed herein. All such variations and modifications areintended to fall within the scope of this disclosure. As such, thedepiction and/or description of an order for various steps should not beunderstood to require a particular order of execution for those steps,unless required by a particular application, or explicitly stated orotherwise clear from the context.

The methods and/or processes described above, and steps associatedtherewith, may be realized in hardware, software or any combination ofhardware and software suitable for a particular application. Thehardware may include a general-purpose computer and/or dedicatedcomputing device or specific computing device or particular aspect orcomponent of a specific computing device. The processes may be realizedin one or more microprocessors, microcontrollers, embeddedmicrocontrollers, programmable digital signal processors or otherprogrammable device, along with internal and/or external memory. Theprocesses may also, or instead, be embodied in an application specificintegrated circuit, a programmable gate array, programmable array logic,or any other device or combination of devices that may be configured toprocess electronic signals. It will further be appreciated that one ormore of the processes may be realized as a computer executable codecapable of being executed on a machine-readable medium.

While the disclosure has been disclosed in connection with the preferredembodiments shown and described in detail, various modifications andimprovements thereon will become readily apparent to those skilled inthe art. Accordingly, the spirit and scope of the present disclosure isnot to be limited by the foregoing examples, but is to be understood inthe broadest sense allowable by law.

The use of the terms “a” and “an” and “the” and similar referents in thecontext of describing the disclosure (especially in the context of thefollowing claims) is to be construed to cover both the singular and theplural, unless otherwise indicated herein or clearly contradicted bycontext. The terms “comprising,” “having,” “including,” and “containing”are to be construed as open-ended terms (i.e., meaning “including, butnot limited to,”) unless otherwise noted. Recitation of ranges of valuesherein are merely intended to serve as a shorthand method of referringindividually to each separate value falling within the range, unlessotherwise indicated herein, and each separate value is incorporated intothe specification as if it were individually recited herein. All methodsdescribed herein can be performed in any suitable order unless otherwiseindicated herein or otherwise clearly contradicted by context. The useof any and all examples, or exemplary language (e.g., “such as”)provided herein, is intended merely to better illuminate the disclosureand does not pose a limitation on the scope of the disclosure unlessotherwise claimed. No language in the specification should be construedas indicating any non-claimed element as essential to the practice ofthe disclosure.

While the foregoing written description enables one of ordinary skill tomake and use what is considered presently to be the best mode thereof,those of ordinary skill will understand and appreciate the existence ofvariations, combinations, and equivalents of the specific embodiment,method, and examples herein. The disclosure should therefore not belimited by the above described embodiment, method, and examples, but byall embodiments and methods within the scope and spirit of thedisclosure.

What is claimed is:
 1. A method for dynamic spectrum sharing betweenprimary users of a spectrum band and secondary users in a cellularnetwork of a commercial cellular operator, the method comprising:transmitting a spectrum request to a government entity owning afrequency band of interest, wherein the spectrum request includesdesired frequency band parameters, receiving a spectrum band assignmentin response to the spectrum request, wherein the spectrum bandassignment includes a plurality of primary resource blocks, building aradio environment map (REM) relating to local radio conditions sensedwithin a cell in the cellular network of the cellular operator, andallocating the received spectrum band assignment via a resourceoptimization process that is based on at least one of an averageachievable rate of a primary resource block of the spectrum bandassignment, an average demand factor of secondary users within the cell,and the radio environment map.
 2. The method of claim 1, furtherincluding: receiving information from sensors relating to demand of thesecondary users in the cellular network, calculating an average spectrumdemand from the received information, and wherein the spectrum requestis based on the average spectrum demand of the secondary users.
 3. Themethod of claim 2, further wherein the spectrum request includes arequest duration.
 4. The method of claim 1, further including sensingprimary user activity, forming a set of available bands within thefrequency band of interest based on the sensed primary user activity,and wherein the spectrum request includes the formed set of availablebands within the frequency band of interest.
 5. The method of claim 4,further wherein the spectrum request takes into account the quality ofservice requirements of the secondary users.
 6. The method of claim 4,wherein the spectrum band assignment further includes conditions on use.7. The method of claim 4, further wherein the spectrum band assignmentis revocable based upon real-time interference data.
 8. The method ofclaim 1, further including obtaining data from an eGMF to incorporate inthe REM.
 9. The method of claim 1, further wherein the allocation stepincludes first allocating the primary resource blocks to one of a set ofzones of the cell, and then allocating the resources in each zone tosecondary users within the corresponding zone.
 10. The method of claim9, wherein the primary resource blocks are allocated to one of a set ofzones of the cell by calculating a utility for assigning a primaryresource block to a zone, and calculating a fractional utility forassigning that primary resource block to an outer zone rather than acenter zone.
 11. The method of claim 10, further wherein the resourceoptimization process includes finding a sector-band pair which givesmaximum fractional utility.
 12. The method of claim 9, wherein the stepof allocating the resources in each zone to secondary users within thecorresponding zone includes use of a utility function corresponding toeach secondary user.
 13. The method of claim 12, wherein a proportionalfairness algorithm is used and a logarithmic utility function is used.14. The method of claim 12, wherein the step of allocating the resourcesin each zone to secondary users within the corresponding zone includes alinear optimization of resources using integer programming subject to ademand constraint.
 15. A method for dynamic spectrum sharing betweenprimary users of a spectrum band and secondary users in a cellularnetwork of a commercial cellular operator, the method comprising:transmitting a spectrum request to a government entity owning afrequency band of interest, wherein the spectrum request includesdesired frequency band parameters, receiving a spectrum band assignmentin response to the spectrum request, wherein the spectrum bandassignment includes a plurality of primary resource blocks andconditions on use, building a radio environment map (REM) relating tolocal radio conditions sensed within a cell in the cellular network ofthe cellular operator, and allocating the received spectrum bandassignment via a first resource optimization process that allocates theprimary resource blocks to one of a set of zones of the cell based on atleast one of an average achievable rate of a primary resource block ofthe spectrum band assignment, an average demand factor of secondaryusers within the cell, and the radio environment map, and via a secondresource optimization process that allocates the resources in each cellzone to secondary users with the corresponding zone according to apredetermined utility function.
 16. The method of claim 15, furtherincluding: receiving information from sensors relating to demand of thesecondary users in the cellular network, calculating an average spectrumdemand from the received information, and wherein the spectrum requestis based on the average spectrum demand of the secondary users.
 17. Themethod of claim 16, further wherein the spectrum request includes arequest duration.
 18. The method of claim 15, further including sensingprimary user activity, forming a set of available bands within thefrequency band of interest based on the sensed primary user activity,and wherein the spectrum request includes the formed set of availablebands within the frequency band of interest.
 19. The method of claim 4,further wherein the spectrum request includes a request duration.
 20. Asystem for dynamic spectrum sharing between primary users of a spectrumband and secondary users, the system comprising: a cellular network of acommercial cellular operator, sensors for sensing local radio conditionswithin a cell of the cellular network, and a spectrum server fortransmitting a spectrum request to a government entity owning afrequency band of interest, wherein the spectrum request includesdesired frequency band parameters, for receiving a spectrum bandassignment in response to the spectrum request, wherein the spectrumband assignment includes a plurality of primary resource blocks andconditions on use, for building a radio environment map (REM) usinginformation from the sensors, and for allocating the received spectrumband assignment via a resource optimization process that is based on atleast one of an average achievable rate of a primary resource block ofthe spectrum band assignment, an average demand factor of secondaryusers within the cell, and the radio environment map.